Nevertheless, the schema above gave room for some beautiful data like the following image, with some databases and collections ending up having millions of data located in an availability zone probably near you! The schema of the document is not very important other than the fact that the ID should be of type GUID: 3-byte incrementing counter, initialized to a random value.This random value is unique to the machine and process. 5-byte random value generated once per process.4-byte timestamp value, representing the ObjectId’s creation, measured in seconds since the Unix epoch.ObjectId values are 12 bytes in length, consisting of: ObjectIds are small, likely unique, fast to generate, and ordered. That thought alone and the fact that a unique ID through out all databases for each price would be a nice to have, made me decide for a GUID instead of MongoBD’s ObjectId(). The document-oriented database selected was MongoDB, but I always had in mind a future move to Azure Cosmos DB, so avoiding vendor lock was a requirement. Since the data to be stored were fairly simple, I was lead to a design featuring one documentDB per market. Markets would be a dynamic thing, meaning different ones being added every once and a while, and old ones potentially removed. Some time ago I created a project for storing product prices but for multiple markets around the world. Have you ever tried to query MongoDB with a GUID? Well I did and it can be confusing! The following documents were inserted into the artists’ collection: db.artists.Just a small one for today. The following example will help you to understand the problem more precisely: The $group stage is used by the aggregation process to get the separate item values from the collection. In this topic, you will learn to find distinct fields using aggregation operations.
#Mongodb compass query distinct values how to#
Read: How to create the indexes in MongoDB? Distinct query in aggregate MongoDB Note that, The benefits of indexes, when we have a large dataset and we want to find out distinct fields on the time with the help of indexes we can easily retrieve the distinct documents fields. We have successfully retrieved the distinct fields using an index. The find() method will use to return the documents of the collection.ĭistinct fields in MongoDB using an index The following documents were inserted into the inventory collection. Now, You will more understand with the help of an example. So, In this topic, you will learn to apply the distinct query with conditions. Sometimes we have to apply the condition using the distinct method to find a particular document. We have successfully retrieved the distinct value from the collection.Īlso, check: MongoDB Auto Increment ID Distinct query in MongoDB with condition Return all the fields of the fname column.db.students.insertMany([Īfter that, we will apply the below query to return the distinct name (fname) of all the students present in the collection: db.student.distinct("fname") The following documents were inserted into the students’ collection. You will more understand this with the help of an example.
In this topic, you will learn to find the distinct values for a given field across a single collection and return the result in an array. Note, you will the aggregation pipeline to retrieve distinct values using the $group operator. Optional, A document that specifies the options. The field name for which you want to return distinct values.Ī query that specifies the documents from which to retrieve the distinct values. The command contains the following fields: parameter Syntax: db.collection.distinct(field, query, options)
The results document also contains an embedded document with query statistics and the query plan. The distinct method will return a document that contains an array of the distinct values. MongoDB finds the distinct values for a defined field over a single collection.
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